TIM-8315: v1

Sanchez, P. M. S., Valero, J. M. J., Celdran, A. H., Bovet, G., Perez, M. G., & Perez, G. M. (2021). A Survey on device behavior fingerprinting: Data sources, techniques, application scenarios, and datasets. IEEE Communications Surveys & Tutorials, Communications Surveys & Tutorials, IEEE, IEEE Commun. Surv. Tutorials, 23(2), 1048–1077.
This journal article describes the implications of device interconnectedness and the cybersecurity threats that are expanding as a result, Specifically, the authors provide a comprehensive review of the device types, behavioral data, and processing and evaluation techniques used by the most recent and representative research works dealing with two major scenarios: device identification and device misbehavior detection.

Zhou, S., Liu, J., Zhong, X., & Zhao, W. (2021). Named entity recognition using BERT with whole world masking in cybersecurity domain. 2021 IEEE 6th International Conference on Big Data Analytics (ICBDA), Big Data Analytics (ICBDA), 2021 IEEE 6th International Conference On, 316–320.
This journal article describes how the amount of cybersecurity data grows quickly on the Internet, however, most of them are textual unstructured data, which is hard for security analysts to understand in time and is not suitable for automated security systems to directly use. The automated and real-time switching of cybersecurity information from unstructured text sources to structured representations can help the cyber threat intelligence analysis know the cyber situation better.

Sun, N., Zhang, J., Rimba, P., Gao, S., Zhang, L. Y., & Xiang, Y. (2019). Data-Driven cybersecurity incident prediction: A survey. IEEE Communications Surveys & Tutorials, Communications Surveys & Tutorials, IEEE, IEEE Commun. Surv. Tutorials, 21(2), 1744–1772.
This journal article explains the changes in the threat landscape with the increasing scale and high-profile cybersecurity incidents related to public data. Research communities and industries have begun proposing cybersecurity incident prediction schemes by utilizing different types of data sources, including organization’s reports and datasets, network data, synthetic data, data crawled from webpages, and data retrieved from social media.

Masip-Bruin, X., Marín-Tordera, E., Ruiz, J., Jukan, A., Trakadas, P., Cernivec, A., Lioy, A., López, D., Santos, H., Gonos, A., Silva, A., Soriano, J., & Kalogiannis, G. (2021). Cybersecurity in ICT supply chains: Key challenges and a relevant architecture. Sensors (Basel, Switzerland), 21(18).
Optional Resource: This journal article describes the imminent threats to the ICT supply chain and the need to develop cybersecurity solutions that utilize big data and intelligent decision-making.

Saiz-Alvarez, J. M., & Leal, G. C. (2017). Cybersecurity best practices and cultural change in global business: Some perspectives from the european union. In G. Afolayan, & A. Akinwale (Ed.), Global Perspectives on Development Administration and Cultural Change (pp. 48-73). IGI Global.
Optional Resource: Read Chapter 3: This chapter discusses how the adoption of best practices to increase cybersecurity in business affects the cultural value of the company. Primarily focused on the European Union, the chapter defines and analyzes both the impact of cyber security on the global business conducted in the European Union and its relation to cloud computing.